Covid Report for Family
April 17, 2020
Background
Notes and format last updated Apr 16, 2020
- This page shows COVID data broken down into regions that affect our family. It pulls from publicly available raw data from the NY Times, which is reported daily. It’s on a one-day lag, so when you see this report, the most recent day included will be that reported the day prior.
- The table of contents above summarizes the major sections and can be used to jump to those sections.
- Each major section is then divided into tabs to allow you to more easily shuffle between geographies and metrics.
- If you open on your phone, I don’t believe the tabs will work, so you’ll just see the page as one long, continuous document.
- More detailed descriptions and context can be found in each section.
Growth rates
Heat maps
- The two heat maps below compare how quickly total cases or deaths have grown at various times in our respective geopgraphies.
- The first plot compares growth rate for total cases; the second, growth rate for total deaths.
- The metric used is doubling time, by which I mean how quickly total cases or deaths are doubling.
- The plots track that doubling time at each date for our geographies. Darker colors reflect shorter doubling times, and thus periods of faster growth.
- You can use the plots to track each geography over time and to compare the geographies to one another.
- You can also compare the cases and death charts, to see how faster periods of death growth follow faster periods of case growth.
Plots of cases
- This section charts the growth rate of both total and new cases for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total cases and new cases.
- There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
- Each of these two lines is a rolling three-day average of daily growth rates for that particular metric.
- For total cases, the trendlines will be a bit smoother and more consistent. We want to see these decline (and almost all are), but they can’t go below zero because total cases can never go down. We at least want them to get as close to zero as possible.
- For new cases, the lines are a bit bumpier, in particular for states. While the trends aren’t as smooth, we want to watch for them to get consistently below zero and stay there. That means that we are consistently seeing fewer new cases on a daily basis and that we’re on the other side of the “apex.”
U.S.
Our states
Plots of deaths
- This section charts the growth rate of both total and new deaths for each of our respective geographies. Each geography has its own chart, and then that chart will have a trendline for total deaths and new deaths.
- There are only plots for the U.S. and states because the numbers for the counties are too small to generate worthwhile trendlines in this section.
- Each of these two lines is a rolling three-day average of daily growth rates for that particular metric.
- For total deaths, the trendlines will be a bit smoother and more consistent. We want to see these decline (and almost all are), but they can’t go below zero because total deaths can never go down. We at least want them to get as close to zero as possible.
- For new deaths, the lines are a bit bumpier, in particular for states. While the trends aren’t as smooth, we want to watch for them to get consistently below zero and stay there. That means that we are consistently seeing fewer new deaths on a daily basis and that we’re on the other side of the “apex.”
U.S.
Our states
By population rankings
This section tracks metrics for states and counties normalized for population (number of cases or deaths per million residents), and then compares these figures both for our geographies and the country overall.
States
- This section shows tables ranking all 50 states for per populations rates of total cases, new cases, total deaths, and new deaths.
- For each metric, in addition to the tables, the trends for the top states are plotted over time.
- We only plot the top ten states for each metric so that the plots aren’t too crowded. But you can view the full 50-state rankings in the tables.
Total confirmed cases
Table of total confirmed cases per million residents (all 50 states)
## state casesPerMillion
## 1: New York 11,426.0
## 2: New Jersey 8,479.0
## 3: Louisiana 4,846.0
## 4: Massachusetts 4,668.0
## 5: Connecticut 4,455.0
## 6: Rhode Island 3,622.0
## 7: District of Columbia 3,329.0
## 8: Michigan 2,915.0
## 9: Pennsylvania 2,211.0
## 10: Delaware 2,130.0
## 11: Illinois 2,030.0
## 12: Maryland 1,783.0
## 13: Colorado 1,506.0
## 14: South Dakota 1,481.0
## 15: Georgia 1,473.0
## 16: Washington 1,464.0
## 17: Indiana 1,417.0
## 18: Vermont 1,230.0
## 19: Mississippi 1,217.0
## 20: Florida 1,086.0
## 21: Nevada 1,078.0
## 22: Alabama 898.0
## 23: Tennessee 891.0
## 24: New Hampshire 890.0
## 25: Idaho 855.0
## 26: Utah 836.0
## 27: Missouri 832.0
## 28: Virginia 807.0
## 29: South Carolina 763.0
## 30: New Mexico 761.0
## 31: Ohio 719.0
## 32: California 712.0
## 33: Iowa 678.0
## 34: Wisconsin 665.0
## 35: Oklahoma 595.0
## 36: Maine 592.0
## 37: Texas 583.0
## 38: Arizona 581.0
## 39: Nebraska 565.0
## 40: Kansas 547.0
## 41: Kentucky 543.0
## 42: Arkansas 536.0
## 43: North Carolina 520.0
## 44: North Dakota 515.0
## 45: Wyoming 511.0
## 46: West Virginia 412.0
## 47: Oregon 411.0
## 48: Alaska 407.0
## 49: Montana 388.0
## 50: Hawaii 377.0
## 51: Minnesota 339.0
## 52: Puerto Rico 326.0
## 53: American Samoa <NA>
## 54: Guam <NA>
## 55: Northern Mariana Islands <NA>
## 56: Virgin Islands <NA>
## state casesPerMillion
New confirmed cases
Table of new cases per million residents: rolling 3-day average (all 50 states)
## state casesNewPerMillion
## 1: New York 466
## 2: New Jersey 402
## 3: Rhode Island 271
## 4: Massachusetts 256
## 5: Connecticut 234
## 6: District of Columbia 186
## 7: South Dakota 166
## 8: Michigan 121
## 9: Louisiana 108
## 10: Delaware 107
## 11: Pennsylvania 104
## 12: Maryland 101
## 13: Illinois 97
## 14: Georgia 79
## 15: Mississippi 76
## 16: Indiana 64
## 17: Colorado 56
## 18: New Hampshire 46
## 19: Iowa 45
## 20: Virginia 44
## 21: Ohio 41
## 22: Alabama 40
## 23: New Mexico 40
## 24: Missouri 39
## 25: Nebraska 38
## 26: Florida 36
## 27: Utah 33
## 28: California 32
## 29: South Carolina 31
## 30: Nevada 30
## 31: Tennessee 29
## 32: Kentucky 28
## 33: Texas 28
## 34: North Dakota 27
## 35: Washington 26
## 36: Wisconsin 25
## 37: Arizona 24
## 38: Kansas 24
## 39: Maine 24
## 40: Oklahoma 24
## 41: North Carolina 21
## 42: West Virginia 18
## 43: Arkansas 16
## 44: Minnesota 15
## 45: Puerto Rico 14
## 46: Idaho 13
## 47: Oregon 12
## 48: Wyoming 12
## 49: Alaska 10
## 50: Vermont 10
## 51: Hawaii 7
## 52: Montana 6
## 53: American Samoa <NA>
## 54: Guam <NA>
## 55: Northern Mariana Islands <NA>
## 56: Virgin Islands <NA>
## state casesNewPerMillion
Total deaths
Table of total deaths per million residents (all 50 states)
## state deathsPerMillion
## 1: New York 626
## 2: New Jersey 396
## 3: Connecticut 272
## 4: Louisiana 248
## 5: Michigan 209
## 6: Massachusetts 180
## 7: District of Columbia 114
## 8: Rhode Island 99
## 9: Illinois 85
## 10: Washington 77
## 11: Indiana 70
## 12: Pennsylvania 67
## 13: Colorado 61
## 14: Georgia 57
## 15: Maryland 57
## 16: Vermont 56
## 17: Delaware 53
## 18: Nevada 46
## 19: Mississippi 43
## 20: Ohio 33
## 21: Oklahoma 33
## 22: Wisconsin 33
## 23: Florida 31
## 24: Kentucky 29
## 25: Alabama 27
## 26: Kansas 27
## 27: Missouri 27
## 28: New Hampshire 25
## 29: California 24
## 30: Virginia 24
## 31: Idaho 22
## 32: South Carolina 21
## 33: Tennessee 21
## 34: Arizona 20
## 35: Maine 20
## 36: New Mexico 20
## 37: Iowa 19
## 38: Puerto Rico 17
## 39: Minnesota 16
## 40: Oregon 15
## 41: Texas 14
## 42: North Carolina 13
## 43: Arkansas 12
## 44: Nebraska 12
## 45: North Dakota 11
## 46: Alaska 9
## 47: South Dakota 7
## 48: West Virginia 7
## 49: Hawaii 6
## 50: Montana 6
## 51: Utah 6
## 52: Wyoming 3
## 53: American Samoa <NA>
## 54: Guam <NA>
## 55: Northern Mariana Islands <NA>
## 56: Virgin Islands <NA>
## state deathsPerMillion
New deaths
Table of new deaths per million residents: rolling 3-day average (all 50 states)
## state deathsNewPerMillion
## 1: New Jersey 40
## 2: New York 36
## 3: Connecticut 34
## 4: Louisiana 19
## 5: Massachusetts 19
## 6: Michigan 16
## 7: District of Columbia 13
## 8: Rhode Island 10
## 9: Illinois 7
## 10: Pennsylvania 7
## 11: Indiana 6
## 12: Georgia 4
## 13: Maryland 4
## 14: Delaware 3
## 15: Mississippi 3
## 16: Nevada 3
## 17: Ohio 3
## 18: Vermont 3
## 19: Alabama 2
## 20: California 2
## 21: Colorado 2
## 22: Florida 2
## 23: New Hampshire 2
## 24: New Mexico 2
## 25: Oklahoma 2
## 26: Virginia 2
## 27: Washington 2
## 28: Wisconsin 2
## 29: Arizona 1
## 30: Idaho 1
## 31: Iowa 1
## 32: Kansas 1
## 33: Kentucky 1
## 34: Maine 1
## 35: Minnesota 1
## 36: Missouri 1
## 37: North Carolina 1
## 38: Puerto Rico 1
## 39: South Carolina 1
## 40: Tennessee 1
## 41: Texas 1
## 42: Alaska 0
## 43: Arkansas 0
## 44: Hawaii 0
## 45: Montana 0
## 46: Nebraska 0
## 47: North Dakota 0
## 48: Oregon 0
## 49: South Dakota 0
## 50: Utah 0
## 51: West Virginia 0
## 52: Wyoming 0
## 53: American Samoa <NA>
## 54: Guam <NA>
## 55: Northern Mariana Islands <NA>
## 56: Virgin Islands <NA>
## state deathsNewPerMillion
Counties
- This section focuses on the county level. It shows tables with our counties ranked by percentile of U.S. counties for per population rates of total cases and total deaths.
- Each table also shows the top five counties in the country in addition to our counties, for added perspecive.
- In addition to the tables, our counties’ percentile for both total cases and total deaths are plotted over time.
Confirmed cases
Table showing total cases per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
## county state casesPerMillion rawRanking percentile
## 1: New York New York 75,610 1 99
## 2: Rockland New York 26,864 2 99
## 3: Westchester New York 22,561 3 99
## 4: Nassau New York 20,467 4 99
## 5: Blaine Idaho 20,286 5 99
## 6: Davidson Tennessee 2,247 174 94
## 7: Richland South Carolina 1,393 355 88
## 8: Pierce Washington 1,176 434 86
## 9: York South Carolina 530 1072 65
## 10: Orange California 449 1257 59Our county percentiles over time 
Deaths
Table showing total deaths per million and percentile for all US counties. Includes our counties and the top 5 in the US for perspective.
## county state deathsPerMillion rawRanking percentile
## 1: New York New York 5,300 1 99
## 2: Randolph Georgia 1,623 2 99
## 3: Terrell Georgia 1,407 3 99
## 4: Mitchell Georgia 1,006 4 99
## 5: Dougherty Georgia 1,000 5 99
## 6: Pierce Washington 33 601 80
## 7: Richland South Carolina 31 626 80
## 8: Davidson Tennessee 27 699 77
## 9: York South Carolina 11 1002 68
## 10: Orange California 8 1049 66Our county percentiles over time 
Raw counts
- This section shows the raw counts over time for the U.S., our states, and our counties for four categories:
- Total confirmed cases: This is the cumulative total of cases reported.
- New confirmed cases: This is the number of new cases reported on each respective date.
- Total deaths: This is the cumulative total of deaths reported.
- New deaths: This is the number of new deaths reported on each respective date.
Total confirmed cases
U.S.
Our states
Our counties
New confirmed cases
U.S.
Our states
Our counties
Total deaths
U.S.
Our states
Our counties
New deaths
U.S.
Our states
Our counties
Stay-at-home comparisons
- This section is a work in progress. It’s exploring what effect stay-at-home orders have on spread. It’s inherentely messy because some states have localized orders but not orders for their full state and because states implemented the orders at different times.
- The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
- So far, this view doesn’t show if these orders are “working” or not. Instead, the biggest takeaway from the current plot is that the states that implemented orders are reacting to having worse spread, which is why the case rate is so much higher at the start for them. As a state decides it has a problem and implements an order, it joins the grouping of states with orders and drives the rate up for that group.
- Over time (if the policies work), what we’d expect is that the line for the group with orders flattens a bit, but we’ll see. It also may become moot if all states issue orders.
- The second plot is new and is attempting to track the progress normalized for how long each state has had the order. It shows the average of the ratio for each state of the new cases for any given day to the number of new cases on the day the order was enacted. If the orders are working, over time this line should come back down…but it isn’t there yet.
- The first plot shows a rolling 3-day average of new cases per million residents, averaged across 2 groups of states – those with a state-wide stay-at-home order in effect and those without. The size of the dots reflect the number of states in each group for each given day (so the dots are getting bigger over time for the group with orders, as more states implement those orders).
